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Record W4389849156 · doi:10.1016/j.yjpso.2023.100112

Advancing care coordination & patient and family engagement in pediatric surgery through enhanced recovery after surgery® protocols

2023· article· en· W4389849156 on OpenAlexaff
Jennifer Lam, Natashia M. Seemann

Bibliographic record

VenueJournal of Pediatric Surgery Open · 2023
Typearticle
Languageen
FieldMedicine
TopicEnhanced Recovery After Surgery
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsMedicineSurgeryGeneral surgery

Abstract

fetched live from OpenAlex

The uptake of pediatric Enhanced Recovery After Surgery (ERAS®) protocols has gradually increased over the years. While many teams have accepted ERAS® protocols for their improvement in clinical outcomes, there are further domains of care that may be strengthened by the adoption of ERAS®. Enhanced Recovery After Surgery® principles provide the framework for coordinating care among the increasingly complex clinical team required to look after pediatric patients. Engaging our pediatric patients and their families throughout the ERAS® process has multiple benefits. Involving patients in the development and implementation process of ERAS® protocols creates more robust guidelines. In addition, engaged patients have greater compliance to recommendations and improved outcomes. The adoption of pediatric ERAS® guidelines enhances pediatric surgical outcomes, establishes strong teamwork, communication and care coordination and reinforces the patient and family needs as a top priority.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.025
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.045
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0040.004
Open science0.0020.013
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0060.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.043
GPT teacher head0.323
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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